| name | surrealql-performance |
| description | Optimize SurrealDB performance through record ID and key design, indexing strategy, and computed/derived fields. Use when queries are slow, when designing record IDs for locality and range scans, choosing between standard/unique/full-text/vector indexes, verifying index usage with EXPLAIN, or deciding whether to precompute values with computed fields, views, or events. Triggers: slow query, performance, record id design, range scan, DEFINE INDEX, EXPLAIN, computed field, FUTURE, DEFINE TABLE AS SELECT. |
| metadata | {"author":"surrealdb","version":"0.1.0"} |
SurrealQL Performance
Techniques for making SurrealDB queries fast: structuring record IDs and keys
for data locality, choosing and verifying the right indexes, and precomputing
values with computed fields and views instead of recomputing them on every read.
Target the latest stable SurrealDB release. Confirm version-sensitive syntax
(record ranges, COMPUTED fields, FULLTEXT index options) against
https://surrealdb.com/docs, and validate examples with surreal validate. See
the surrealql skill for version detection.
When to use this skill
- A query is slow or scans more records than expected
- Designing record IDs to support efficient lookups and range scans
- Choosing between standard,
UNIQUE, full-text SEARCH, or vector indexes
- Confirming whether an index is actually used (
EXPLAIN)
- Deciding whether to store a derived value vs. compute it on read
Topic map
Top rules
- Design IDs for access patterns. Record IDs are stored in sorted order. Put
the most selective, range-friendly component first (e.g.
weather:['London', d'2025-02-13T05:00Z']) so related records sit together and
range queries avoid full-table scans. See references/keys.md.
- Prefer record ranges over
WHERE on the ID. SELECT * FROM person:1..1000
uses key ordering directly; filtering with WHERE after a full scan does not.
- Index the fields you filter, sort, or join on — but no more. Every index
adds write cost. Order composite index fields from most to least selective and
to match your query's filter/sort order. See references/indexing.md.
- Verify, don't assume. Run
EXPLAIN (or EXPLAIN FULL) to confirm a query
uses the index you expect before concluding it is optimized.
- Precompute expensive, read-heavy values. Use computed fields, a
DEFINE TABLE ... AS SELECT view, or a DEFINE EVENT to maintain derived data
rather than recomputing aggregates on every query. See
references/computed-fields.md.
- Use bound parameters. Parameterized queries are safer and let the engine
reuse query plans.
